A disruption management system for automotive inbound networks: concepts and challenges

• Published in: EURO Journal on Transportation and Logistics Vol. 7; no. 1; pp. 25 - 56
• Main Authors: Meyer, Anne, Sejdovic, Suad, Glock, Katharina, Bender, Matthias, Kleiner, Natalja, Riemer, Dominik
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Elsevier B.V 01.03.2018; Springer Berlin Heidelberg; Elsevier Limited
• Subjects: Automobile industry; Automotive engineering; Automotive inbound networks; Business and Management; Complex event processing; Disruption; Errors; Logistics; Management Science; Online optimization; Operations Research; Operations Research/Decision Theory; Optimization; Real-time analytics; Research Paper; Transport and logistics; Transport processes; Online optimization; Transport and logistics; Automotive inbound networks; Real-time analytics; Complex event processing
• ISSN: 2192-4376; 2192-4384; 2192-4384
• DOI: 10.1007/s13676-017-0108-5

Production processes in the automotive industry are highly dependent on reliable inbound logistics processes, because in lean production systems delays or mistakes often result in expensive interruptions of production processes. However, transport processes are always subject to unavoidable disturbances, delays, or mistakes. The goal of the research project ProveIT is to provide an IT system improving the transparency by monitoring transport processes in real-time: deviations from the transport plans are identified predictively, and classified dynamically as disruptions if they have negative impacts on the subsequent processes. If a disruption occurs, the operations managers are provided with mitigation actions automatically generated by escalation-based online optimization algorithms. In this contribution, we introduce the use cases, the architecture and main concepts of the ProveIT disruption management system, and report on challenges faced during field experiments with our application partners, Bosch, ZF, and Geis.